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A Bayesian large deviations probabilistic interpretation and justification of empirical likelihood

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  • Grendar, Marian
  • Judge, George G

Abstract

In this paper we demonstrate, in a parametric Estimating Equations setting, that the Empirical Likelihood (EL) method is an asymptotic instance of the Bayesian non-parametric Maximum-A-Posteriori approach. The resulting probabilistic interpretation and justifcation of EL rests on Bayesian non-parametric consistency in L-divergence.
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Suggested Citation

  • Grendar, Marian & Judge, George G, 2007. "A Bayesian large deviations probabilistic interpretation and justification of empirical likelihood," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt3v88z9xf, Department of Agricultural & Resource Economics, UC Berkeley.
    • Handle: RePEc:cdl:agrebk:qt3v88z9xf
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    Cited by:

    1. Grendar, Marian & Judge, George G. & Niven, R.K., 2007. "Large Deviations Approach to Bayesian Nonparametric Consistency: the Case of Polya Urn Sampling," CUDARE Working Papers 6056, University of California, Berkeley, Department of Agricultural and Resource Economics.

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